The first two panels show moderate but persistent overresponse to current weather and supply information, with implicit coefficient estimates lying closer to [+ or -]0.
There may be a slight bias toward overresponse in the High Noise treatment and toward underresponse to the more important stimulus (Supply) in the Asymmetric treatment.
Underresponse to the more important variable (as in Figure 4) and overresponse to the other variable are quite prevalent in the Asymmetric treatment.
00), and significant overresponse to both variables in the High Noise treatment (p = 0.
Recall from Figure 2 the impression that moderate but shrinking overresponse is quite typical at this point.
The Asymmetric treatment, however, significantly lowered scores and pushed subjects significantly toward underresponse to the more important information and (insignificantly) toward overresponse to the less important information.
013 and would tend to shift the classifications very slightly toward overresponse.
Indeed, the relevant test would indicate marginally significant overresponse (to the second variable in the No History treatment, p = 0.
Tests allowing a nonzero intercept term a0 reached different conclusions only for the Asymmetric treatment, where the marginally significant overresponse to the less important news disappeared.
Census benchmarks on age, sex, race/ethnicity, income and household size to reduce potential bias due to underresponse or overresponse
in categories within these demographic variables.